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  • br Discussion br This study

    2020-08-12


    Discussion
    This study sought to identify genes potentially co-expressed with the cyclin E oncogene in gastric
    Table 4
    Top 19 genes with highest connectivity in predicted interaction network.
    Gene Symbol Connectivity (Degree) Pearson Co. Spearman Co.
    Pearson Co.: Pearson correlation coefficient; Spearman Co.:
    Spearman correlation coefficient.
    cancer and to clarify the probable regulatory mecha-nisms. By querying the public TCGA stomach adeno-carcinoma sequencing data, 78 genes were implicated possibly being co-expressed with cyclin E. Pearson correlation coefficient evaluation of the correlation be-
    tween the co-expression of these genes and cyclin E used a coefficient threshold set at 0.4.19,20 The 78
    These non-coding genes and their transcripts (i.e. non-coding RNAs) are important for regulating gene tran-scription or translation, and their changes in expression level often have a strong influence on phenotype. However, due to their relatively low coefficients (<0.4) and weak correlations with cyclin E, the focus shifted from the non-coding genes to the protein-coding genes with the highest correlation. The top 15 of these genes comprise those implicated in the development of gastric cancer. Jun et al21 reported the association of UQCRFS1 amplification with gastric cancer progression and un-favorable prognosis. Yu et al22 subsequently demon-strated that zinc finger protein 331 may suppress gastric carcinogenesis by down-regulating UQCRFS1 as well as other genes involved in MethoxyX04 promotion. Kaneko et al23 reported that NUF2 (also known as CDCA1) is frequently upregulated in gastric cancer, and targeting this gene by small interfering RNA may induce cell cycle arrest and apoptosis in gastric cancer cells in vitro. Similar results have been reported for PSRC1 and NEK2.24e26 GO annotation is a powerful method to help
    understand cellular participation and function of a set of genes with potential allocations.27,28 GO anno-
    tation of the 73 protein coding genes potentially co-expressed with cyclin E showed that these genes were mostly enriched in the promotion of the cell cycle and in mitosis. These results strongly suggest that genes co-expressed with cyclin E may have a similar function in promoting cell proliferation and gastric cancer progression.
    Fig. 3. Transcription factor enrichment analysis of 19 predicted cyclin E co-expressing genes. Percentage of genes enriched for each transcription factor is plotted on the left axis and -log10P on the right axis. The dotted horizontal line represents the P ¼ 0.05 threshold.
    Fig. 4. Western blotting analysis of cyclin E and NF-YA protein expression levels in 22 pairs of gastric cancer specimens (CA) and their non-cancerous counterparts (NC). (A) Representative results of cyclin E and NF-YA protein expression levels in CA and NC samples from one patient. (B) Statistical analysis of cyclin E and NF-YA expression in 22 pairs of CA and NC samples. The gray scale analysis of each band was performed using ImageJ software, and gray scale of each band was normalized to the mean value of that in NC group. P value was calculated automatically. aCompared with NC, P < 0.001. (C) Correlation analysis of cyclin E and NF-YA protein expression based on Western blotting results.
    We further hypothesized that these genes playing similar roles and with potential correlation might be involved or regulated by the same signal regulatory network, and their transcription might be regulated by some shared transcriptional factors. MethoxyX04 To reveal the interaction network of proteins coded by the 73 discovered cyclin E co-expressing protein coding genes, we employed the STRING online analysis platform to examine the interactions that were 
    Fig. 5. KaplaneMeier survival estimates. (A) KaplaneMeier curve analysis of overall survival of patients with different cyclin E expression levels, P ¼ 0.0417. (B) KaplaneMeier curve analysis of overall survival of patients with different NF-YA expression levels, P ¼ 0.0325.
    experimentally verified or predicted by an algorithm. We further analyzed the topological structure of the summarized interaction network using Cytoscape software.29e32 We discovered 19 genes at the central of the interaction network of the 73 genes based on the topological structure. Genes with a degree of connection exceeding 15, except for SPAG5, have been previously linked to the development of gastric cancer.33e37 The result demonstrates the robustness of our bioinformatics analysis methods and reveals a gastric cancer-promoting interaction network associated with cyclin E.
    A transcription factor enrichment prediction per-formed using the FunRich software identified a novel transcription factor, NF-YA, that might be the most significant transcription factor associated with genes in this interaction network that we have discovered. The association of NF-YA with cancer progression has been preliminarily reported in other cancer models.38e41 The role of NF-YA seems to mainly involve facilitating the transcription of genes in the cell cycle and cell proliferation. Previously, a role of NF-YA in gastric cancer has not been defined.42e44 NF-YA is a subunit of the NF-Y heterotrimer, which has been suggested to aid